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Titlebook: Data Science – Analytics and Applications; Proceedings of the 2 Peter Haber,Thomas Lampoltshammer,Manfred Mayr Conference proceedings 2019

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樓主: 淺吟低唱
31#
發(fā)表于 2025-3-26 23:10:26 | 只看該作者
32#
發(fā)表于 2025-3-27 03:49:34 | 只看該作者
Sam Bigeard,Frantz Thiessard,Natalia Grabar, called nodes, and a statistical test to assess the quality of partitioning. A number of publicly available literature examples have been used to test the performance of the method against others that are available in the literature.
33#
發(fā)表于 2025-3-27 09:19:57 | 只看該作者
34#
發(fā)表于 2025-3-27 13:12:27 | 只看該作者
35#
發(fā)表于 2025-3-27 15:12:38 | 只看該作者
The Effectiveness of the Max Entropy Classifier for Feature Selection other classifiers to do the actual classification. Experiments on different natural language processing tasks confirm that the weight-based method is comparable to count-based methods. The number of input features can be reduced considerably while maintaining the classification performance.
36#
發(fā)表于 2025-3-27 18:38:12 | 只看該作者
37#
發(fā)表于 2025-3-27 22:57:27 | 只看該作者
38#
發(fā)表于 2025-3-28 05:44:53 | 只看該作者
39#
發(fā)表于 2025-3-28 07:57:03 | 只看該作者
40#
發(fā)表于 2025-3-28 13:56:14 | 只看該作者
Chance influence in datasets with a large number of features. Such configuration promotes the influence of chance on the learning process as well as on the evaluation. Prior research underlined the problem of generalization of models obtained based on such data. In this paper, we deeply investigate the influence of chance on classification and regression. We
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